Learning word embeddings is an active research area [1]}, [2]}, [3]}, [4]}.
The main idea is to learn a word representation according to its context: the surrounding words [5]}.
The words are projected on a continuous space and those with similar context should be close in this multi-dimensional space.
When word vectors are available, a similarity between two words can be measured by a metric such as a cosine similarity.
